Association of Survival and Immune-Related Biomarkers With Immunotherapy in Patients With Non–Small Cell Lung Cancer

Yu, Yunfang; Zeng, Dongqiang; Ou, Qiyun; Liu, Shengbo; Li, Anlin; Chen, Yongjian; Lin, Daowei; Gao, Qi; Zhou, Haiyu; Liao, Wangjun

doi:10.1001/jamanetworkopen.2019.6879

Cited by 208 publications

(149 citation statements)

References 56 publications

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“…To the best of our knowledge, this is the first study to identify the mutation status of PTPRT as a key predictor of ICI efficacy. We found that PTPRT mutation conferred an elevated TMB and better survival during ICI therapy in pancancer and specifically in melanoma and NSCLC, which collaborated with our previous research 1 showing a pronounced survival and response benefits of ICI among cancer patients with high TMB. PTPRT has not been suggested to be screened for mutations in current widely used gene panels such as Memorial Sloan Kettering (F1CDx).…”

supporting

confidence: 89%

Association of immune checkpoint inhibitor with survival in patients with cancers with protein tyrosine phosphatase receptor T mutation

Lin

et al. 2020

Clinical & Translational Med

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Dear Editor, We and others have shown that the tumor mutation burden (TMB) and several underlying oncogenic alterations could provide clinically predictive implications for immune checkpoint inhibitor (ICI). 1-3 Protein tyrosine phosphatases (PTPs) consist of a variety classes, and most of them are highly mutated in multiple cancers and are closely interact with innate and acquired immunity regulating immune cell activation and differentiation. 4,5 PTP receptor T (PTPRT) has been found to be the most frequently mutated PTP gene in cancers and could predict poor prognosis; 4,6 however, the association of PTPRT mutation with clinical outcomes of ICI remains unknown. Here, we performed a comprehensive pancancer investigation to clinically validate PTPRT mutation as a predictive biomarker for ICI therapy. We collected clinical and PTPRT mutational data quantified by whole exome sequencing of 2129 cancer patients treated with ICI and 10,814 cancer patients without receiving ICI from the cBioPortal, PubMed, and The Cancer Genome Atlas. The study protocol was approved by the ethics committee of the Sun Yat-sen Memorial Hospital of Sun Yat-sen University. The requirement for informed consent of study participants and the permission to use the patient data were waived because the human data were obtained from publicly available datasets. All analyses were performed according to the STROBE guideline from September 18 through October 1, 2019. Overall survival (OS) were primary outcomes, which were computed using the Kaplan-Meier method and were assessed with the log-rank test and the hazard ratio (HR) calculated by the Cox regression model. The TMB in PTPRT wildtype versus mutant groups were compared with Wilcoxon rank-sum tests. All analyses were performed using R (version 3.4.4) and were considered statistically significant if P values < .05. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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supporting

confidence: 89%

Association of immune checkpoint inhibitor with survival in patients with cancers with protein tyrosine phosphatase receptor T mutation

Lin

et al. 2020

Clinical & Translational Med

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“…Earlier studies also showed that some immune genes are signi cantly related to the prognosis of LADC [20]. In addition, other studies have found that immune gene expression should be included in the current multi-gene test to improve the prognosis of patients with LADC [21,22]. However, these studies have not been used to predict the probability of OS in clinical studies.…”

Section: A B 4 Discussionmentioning

confidence: 99%

Development of Prognostic Nomogram Based on Immune Scores in Lung Adenocarcinoma Patients

Xie¹,

Zhang²,

Li³

2020

Preprint

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Background: Immunotherapy has significantly altered the treatment landscape for non-small cell lung cancer (NSCLC).However, there is no report on the prediction of overall survival (OS) of lung adenocarcinoma (LDAC) based on immune score. In this study,we aim to investigate the immune scores of the LADC and the prognosis-related factors and construct a nomogram for prognosis prediction.Methods:A total of 407 cases were included in the study.And the clinicopathological characteristics of patients with LADC and immune scores were download from TCGA database.We used Cox proportional hazards regression models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs).Nomograms were framed from Cox models and internally validated by use of 1000 bootstrap.Model discrimination was assessed by using the concordance index (c-index) and the calibration curve.Results：Patients were divided into groups with low, moderate, or high Subgroups based on immune scores.This study shows that compared with patients with low and intermediate immune scores, only those with high immune scores had significantly improved OS (HR and 95% confidence interval[CI]:0.488 [0.327‐0.730]).The C‐index for OS prediction was 0.707(95% CI, 0.664‐0.750) .The calibration curves for prediction of 3-years and 5-years OS probabilities demonstrated good calibration and discrimination.Conclusions：High immune scores Subgroup is very significantly correlated with better OS in patients with LADC. Moreover, the nomograms for predicting prognosis may help to assess the survival of patients with LADC.

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“…However, while Immunoscore has demonstrated superiority to gold standard TNM classification, its adoption in routine clinical practice has been slow, and predictive performance with respect to specific immunotherapies has not yet been established [17]. Further efforts have been aimed at combining several biomarkers that, due to their independent nature, together may capture different aspects of neoantigenicity and T cell activation and may provide greater predictive and prognostic relevance than each of them individually [18,19]. For example, in a study utilizing whole-exome and RNA sequencing information from the Cancer Genome Atlas, a linear combination of three variables-CD8+ T-cell abundance, TMB, and high PD1 gene expression-resulted in a higher correlation with response to anti-PD-1/PD-L1 therapy across cancer types than the individual components [20].…”

Section: Introductionmentioning

confidence: 99%

Mass Spectrometry-Based Multivariate Proteomic Tests for Prediction of Outcomes on Immune Checkpoint Blockade Therapy: The Modern Analytical Approach

Grigorieva

Asmellash

Net

et al. 2020

IJMS

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The remarkable success of immune checkpoint inhibitors (ICIs) has given hope of cure for some patients with advanced cancer; however, the fraction of responding patients is 15–35%, depending on tumor type, and the proportion of durable responses is even smaller. Identification of biomarkers with strong predictive potential remains a priority. Until now most of the efforts were focused on biomarkers associated with the assumed mechanism of action of ICIs, such as levels of expression of programmed death-ligand 1 (PD-L1) and mutation load in tumor tissue, as a proxy of immunogenicity; however, their performance is unsatisfactory. Several assays designed to capture the complexity of the disease by measuring the immune response in tumor microenvironment show promise but still need validation in independent studies. The circulating proteome contains an additional layer of information characterizing tumor–host interactions that can be integrated into multivariate tests using modern machine learning techniques. Here we describe several validated serum-based proteomic tests and their utility in the context of ICIs. We discuss test performances, demonstrate their independence from currently used biomarkers, and discuss various aspects of associated biological mechanisms. We propose that serum-based multivariate proteomic tests add a missing piece to the puzzle of predicting benefit from ICIs.

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Association of Survival and Immune-Related Biomarkers With Immunotherapy in Patients With Non–Small Cell Lung Cancer

Abstract: This meta-analysis examines whether differences in biomarkers, such as programmed cell death ligand 1 (PD-L1) expression and tumor mutation burden, are associated with improved response to immunotherapy and survival in patients with advanced non–small cell lung cancer (NSCLC).

Cited by 208 publications

References 56 publications

Association of immune checkpoint inhibitor with survival in patients with cancers with protein tyrosine phosphatase receptor T mutation

Association of immune checkpoint inhibitor with survival in patients with cancers with protein tyrosine phosphatase receptor T mutation

Development of Prognostic Nomogram Based on Immune Scores in Lung Adenocarcinoma Patients

Mass Spectrometry-Based Multivariate Proteomic Tests for Prediction of Outcomes on Immune Checkpoint Blockade Therapy: The Modern Analytical Approach

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